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I've trained my rasa nlu model in a way that It recognizes the content in between square brackets as pst entity. For the training part, I had covered both the scenarios with more than 50 examples.

There are two scenarios(only space difference):

1. When I pass http://www.google.comm, 1283923, [9283911,9309212,9283238], it is considering only [ bracket as the pst entity.




2. When I pass http://www.google.comm, 1283923, [9283911, 9309212, 9283238], it is working fine and recognizing [9283911, 9309212, 9283238] as the pst entity as expected.

For the scenario 1, I've tried all the possible pipelines, but it only recognizes the first square bracket [ as the pst entity

In the response, I am getting this output:

 'intent': 
 'name': None,
 'confidence': 0.0
 ,
 'entities': [
 
 'start': 0,
 'end': 22,
 'value': 'http://www.google.comm',
 'entity': 'url',
 'confidence': 0.8052099168500071,
 'extractor': 'ner_crf'
 ,
 
 'start': 24,
 'end': 31,
 'value': '1283923',
 'entity': 'defect_id',
 'confidence': 0.8334249141074151,
 'extractor': 'ner_crf'
 ,
 
 'start': 33,
 'end': 34,
 'value': '[',
 'entity': 'pst',
 'confidence': 0.5615805162522188,
 'extractor': 'ner_crf'
 
 ],
 'intent_ranking': ,
 'text': 'http://www.google.comm, 1283923, [9283911,9309212,9283238]'

So, Can anyone tell me what I am missing in the configuration? The problem is happening because of spacing only, and my model should have the knowledge of spacing as I am providing the training data with both scenarios.

It is good idea to use Regex for your purpose. Rasa NLU supports extraction of Entities by Regex. Normal NLU training data will have something like below

 "rasa_nlu_data": 
 "common_examples": [
 
 "text": "Hi",
 "intent": "greet",
 "entities": 
 ]
 
 

You can provide Regex data for training as below in the NLU json file.

 "rasa_nlu_data": 
 "regex_features": [
 
 "name": "pst",
 "pattern": "[..*]"
 ,
 ]
 

Reference: Regular Expression in Rasal NLU